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http://flytrap.med.yale.edu/

The FlyTrap database presents the current results of large scale protein trapping screens that provide both information on which cells express each tagged gene, and subcellular localization of GFP-tagged proteins. Expression is under the control of endogenous promoter and enhancer elements, allowing for visualization of normal expression patterns. Drosophila proteins tagged with Green Fluorescent Protein (GFP) were created by insertion into genes of an artificial exon encoding GFP flanked by splice acceptor (SA) and splice donor (SD) sequences so that expression of GFP relies on splicing into mature mRNAs and in-frame fusion.

Proper citation: FlyTrap- GFP Protein Trap Database (RRID:SCR_013354) Copy   

•   Source: SciCrunch Registry

http://proline.bic.nus.edu.sg/dedb/

Database on Drosophila melanogaster exons presented in a splicing graph form. Data is based on release 3.2 of the Drosophila melanogaster genome annotations available at FlyBase. The gene structure information extracted from the annotations were checked, clustered and transformed into splicing graph. The splicing graph form of the gene constructs were then used for classification of the various types of alternative splicing events. In addition, Pfam domains were mapped onto the gene structure. Users can query the database using the query page using BLAST, FlyBase Gene Name, FlyBase Gene Symbol, Pfam Accession Number and Pfam Identifier. This allows users to determine the Drosophila melanogaster homology of their gene using a BLAST search and to visualize the alternative splicing variants if any. Users can also determine genes containing a particular domain using the Pfam Accession Numbers and Identifiers.

Proper citation: Drosophila melanogaster Exon Database (RRID:SCR_013441) Copy   

•   Source: SciCrunch Registry

http://www.dbali.org

DBAli is a database that includes a comprehensive all-against-all comparison of protein structures in the PDB database. It is not currently being updated; however, updates should resume in the near future. All pairwise structural comparisons in DBAli have been obtained using the MAMMOTH program developed in the group of Prof. Angel R. Ortiz. All multiple structure alignments in DBAli have been obtained using the SALIGN command in MODELLER developed in the group of Prof. Andrej Sali.

Proper citation: DBAli. A Database of Structure Alignments. (RRID:SCR_013418) Copy   

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http://rarge.psc.riken.jp/rartf/

Database of complete sets of Arabidopsis transcription factors with a variety of information on Arabidopsis thaliana transcription factor families including: full-length cDNA sequences, Ds-tagged mutants, multiple sequences alignments of family members, phylogenic trees, functional motifs, and so on. In addition, expression profiles of all transcription factor genes are available.

Proper citation: RARTF (RRID:SCR_013457) Copy   

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https://ua.ilab.agilent.com/service_center/show_external/4535?name=analytical-and-biological-mass-spectrometry

Provides equipment and expertise for analysis of variety of biological and small molecules.Services include protein analysis encompassing protein identification, protein and peptide sequence confirmation, intact protein molecular weight determination, complex protein sample analysis, and protein/antibody drug interactions.Developed metabolomics library to support metabolomic and lipidomics analysis. Can identify range of post-translational modifications, determining their presence or absence, as well as quantitating PTMs.Proteomics and small molecule services include workflows for label free,chemical labeling (iTRAQ/TMT) and metabolic labeling (SILAC).Service for molecular synthesis, with monitoring reaction steps,calculating percentage of product, testing for purity, and molecule characterization with high resolution and high mass accuracy.Provides molecular weight and chemical composition determinations, structure elucidations and compound identification analysis or confirmation and accurate mass measurements of synthetic products, measurement of polymers, nucleic acids (DNA/RNA), peptides, proteins, natural products, and assistance with determination of unknowns.

Proper citation: University of Arizona Analytical and Biological Mass Spectrometry Core Facility (RRID:SCR_023370) Copy   

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http://tardis.nibio.go.jp/homstrad/

A curated database of structure-based alignments for homologous protein families. All known protein structure are clustered into homologous families (i.e., common ancestry), and the sequences of representative members of each family are aligned on the basis of their 3D structures using the programs MNYFIT, STAMP and COMPARER. These structure-based alignments are annotated with JOY and examined individually.

Proper citation: HOMSTRAD - Homologous Structure Alignment Database (RRID:SCR_006544) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/PRED-TMR2/

A web server that classifies proteins into two classes from their sequences alone: the membrane protein class and the non-membrane protein class. This may be important in the functional assignment and analysis of open reading frames (ORF''s) identified in complete genomes and, especially, those ORF''s that correspond to proteins with unknown function. The network has a simple hierarchical feed-forward topology and a limited number of neurons which makes it very fast. By using only information contained in 11 protein sequences, the method was able to identify, with 100% accuracy, all membrane proteins with reliable topologies collected from several papers in the literature. Applied to a test set of 995 globular, water-soluble proteins, the neural network classified falsely 23 of them in the membrane protein class (97.7% of correct assignment). The method was also applied to the complete SWISS-PROT database with considerable success and on ORF''s of several complete genomes. The neural network developed was associated with the PRED-TMR algorithm (Pasquier,C., Promponas,V.J., Palaios,G.A., Hamodrakas,J.S. and Hamodrakas,S.J., 1999) in a new application package called PRED-TMR2.

Proper citation: PRED-TMR2 (RRID:SCR_006205) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/l2n/upload/register.php

A web-based software system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system.

Proper citation: Lists2Networks (RRID:SCR_006323) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/PRED-TMR/

A web server that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The algorithm refines a standard hydrophobicity analysis with a detection of potential termini (edges, starts and ends) of transmembrane regions. This allows both to discard highly hydrophobic regions not delimited by clear start and end configurations and to confirm putative transmembrane segments not distinguishable by their hydrophobic composition. The accuracy obtained on a test set of 101 non homologous transmembranes proteins with reliable topologies compares well with that of other popular existing methods. Only a slight decrease in prediction accuracy was observed when the algorithm was applied to all transmembrane proteins of the SwissProt database (release 35).

Proper citation: PRED-TMR (RRID:SCR_006203) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

http://chemistry.st-andrews.ac.uk/staff/jbom/group/databases.html

It is a publicly available web-based database that aims to provide further understanding of protein-ligand interactions. It''s a resource containing biomolecular data, including binding energies, Tanimoto ligand similarity scores and protein sequence similarities of protein-ligand complexes. The PLD contains biomolecular data including calculated binding energies, Tanimoto ligand similarity scores and protein percentage sequence similarities. The database has potential for application as a tool in molecular design.

Proper citation: Protein Ligand Database (RRID:SCR_006980) Copy   

•   Source: SciCrunch Registry

http://ekhidna.biocenter.helsinki.fi/dali/start

Resource out of service. Documented on May, 5th, 2021.The Dali Database is based on all-against-all 3D structure comparison of protein structures in the Protein Data Bank (PDB). The structural neighborhoods and alignments are automatically maintained and regularly updated using the Dali search engine. The Dali Database contains structural alignments of PDB90 versus the full PDB using DaliLite. The data can be viewed interactively here, or downloaded in its entirety Users may search by PDB identifier or keyword.

Proper citation: Dali database (RRID:SCR_006974) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/CCDS/

Database (anonymous FTP) resulting from a collaborative effort to identify a core set of human and mouse protein coding regions that are consistently annotated and of high quality. The long term goal is to support convergence towards a standard set of gene annotations. Collaborators are EBI, NCBI, UCSC, WTSI and the initial results are also available from the participants'''' genome browser Web sites. In addition, CCDS identifiers are indicated on the relevant NCBI RefSeq and Entrez Gene records and in Map Viewer displays of RNA (RefSeq) and Gene annotations on the reference assembly.

Proper citation: Consensus CDS (RRID:SCR_006729) Copy   

•   Source: SciCrunch Registry

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/

A database of interactions between HIV-1 and human proteins published in the peer-reviewed literature. The goal is to provide a concise, yet detailed, summary of all known interactions of HIV-1 proteins with host cell proteins, other HIV-1 proteins, or proteins from disease organisms associated with HIV/AIDS. For each HIV-1 human protein interaction the following information is provided: * NCBI Reference Sequence (RefSeq) protein accession numbers. * NCBI Entrez Gene ID numbers. * Amino acids from each protein that are known to be involved in the interaction. * Brief description of the protein-protein interaction. * Keywords to support searching for interactions. * PubMed identification numbers (PMIDs) for all journal articles describing the interaction. In addition, all protein-protein interactions documented in the database are integrated into Entrez Gene records and listed in the ''HIV-1 protein interactions'' section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication.

Proper citation: HIV-1 Human Protein Interaction Database (RRID:SCR_006879) Copy   

•   Source: SciCrunch Registry

https://myhits.sib.swiss/

Database devoted to protein domains. It is also a collection of tools for the investigation of the relationships between protein sequences and motifs described on them.

Proper citation: MyHits (RRID:SCR_006757) Copy   

•   Source: SciCrunch Registry

http://rkd.ucdavis.edu/interactome.shtml

It was created to host functional genomic information gathered as part of a large NSF funded rice kinase proteomics project. The goal is to integrate disparate data sets into a logical, user friendly format. To accomplish this, they have developed a platform to display user selected functional genomic data on a phylogenetic tree. The RKD also includes an interactive chromosomal map showing the positions of all rice kinases and an interactive protein-protein interaction maps.

Proper citation: Rice Kinase Database (RRID:SCR_006990) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/cuticleDB

A relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the five sequenced genomes where manual annotation has been applied to cuticular proteins: Anopheles gambiae, Apis mellifera, Bombyx mori, Drosophila melanogaster, and Nasonia vitripennis. Some sequences were confirmed as authentic cuticular proteins because protein sequencing revealed that they were present in cuticle; others were identified by sequence homology and other criteria. Entries provides information about whether sequences are putative or authentic cuticular proteins. CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

Proper citation: CuticleDB (RRID:SCR_007045) Copy   

•   Source: SciCrunch Registry

http://www.signaling-gateway.org/molecule/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Relational database of all significant published qualitative and quantitative information on cell signaling proteins. The Molecule Pages database was developed with the specific aim of allowing interactions, and indeed whole pathways, to be modeled. The goal is to filter the data to present only validated information. In addition, the Gateway is the home of Signaling Update, which provides a one-stop overview of the latest and hottest research in cell signaling for both the specialist and non-specialist alike.

Proper citation: UCSD-Nature Signaling Gateway Molecule Pages (RRID:SCR_006907) Copy   

•   Source: SciCrunch Registry

http://www.dddc.ac.cn/pdtd/

It is a dual function database that associates an informatics database to a structural database of known and potential drug targets. PDTD is a comprehensive, web-accessible database of drug targets, and focuses on those drug targets with known 3D-structures. PDTD contains 1207 entries covering 841 known and potential drug targets with structures from the Protein Data Bank (PDB). Drug targets of PDTD were categorized into 15 and 13 types according to two criteria: therapeutic areas and biochemical criteria. The database supports extensive searching function using PDB ID, target name and category, related disease.

Proper citation: Potential Drug Target Database (RRID:SCR_007069) Copy   

•   Source: SciCrunch Registry